Triple
T7463069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miga |
E176297
|
entity |
| Predicate | appearsWith |
P4540
|
FINISHED |
| Object | Sumi |
E176299
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Sumi | Statement: [Miga, appearsWith, Sumi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sumi Context triple: [Miga, appearsWith, Sumi]
-
A.
Sumi
chosen
Sumi is one of the official mascots of the 2010 Winter Olympics in Vancouver, depicted as a mythical animal spirit representing the natural beauty and indigenous cultures of Canada.
-
B.
Sumio
Sumio is a Japanese physicist best known for his pioneering discovery and characterization of carbon nanotubes.
-
C.
Shimotsuki
Shimotsuki was a Japanese destroyer of the Imperial Japanese Navy that served in World War II before being sunk in late 1944.
-
D.
Harumi
Harumi is a waterfront district in Tokyo’s Chūō ward known for its high-rise residential towers and role in the Tokyo 2020 Olympic and Paralympic Village.
-
E.
Yukio
Yukio is a Japanese given name commonly used for males and borne by several notable figures in politics, arts, and entertainment.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c69f21632481908bf83f6c6da897e3 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f3d80ae08190ba383066cf0cb2ce |
completed | March 27, 2026, 9:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c845f494b481908c1860ad1662fa92 |
completed | March 28, 2026, 9:19 p.m. |
Created at: March 27, 2026, 3:39 p.m.